get_scan_reportsGet available reports for a scan_id.
| Name | Required | Description | Default |
|---|---|---|---|
| scan_id | Yes | ||
| report_type | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true, which cover safety. However, the description adds no behavioral context beyond that—it doesn't disclose whether the tool returns a list of report names, report contents, or how report_type alters behavior. There is no contradiction with annotations, but the description contributes minimal value.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no filler or redundancy. Every word is meaningful and the structure is front-loaded with the action and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema and rich annotations, the description is too sparse for a tool with an optional parameter (report_type) and many sibling tools. It fails to explain what 'reports' encompasses or how report_type filters results, so the agent cannot fully determine correct invocation without additional inference.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% and the description only references scan_id, which is already self-explanatory from the schema property name. The optional report_type parameter is not described in the description or schema, so the agent gets no additional meaning beyond the raw parameter names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get available reports for a scan_id' uses a specific verb ('Get') and resource ('available reports') tied to a scan_id, making the core purpose clear. It does not explicitly differentiate from sibling tools like get_scan_result or get_scan_summary, but the naming and phrasing are sufficient for basic distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives or exclusions. The description does not mention how it relates to get_scan_result, get_scan_summary, or get_analyzer_results, and there are no prerequisites or filter instructions, leaving usage ambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Many tools overlap in purpose, particularly the JS fingerprint search functions (e.g., search_js_fingerprint_by_md5 and search_jsfingerprints_by_md5) which are nearly identical. The large number of get_* and search_* tools for various statistics also creates boundary ambiguity.
The verb_noun pattern is mostly followed, but there are significant inconsistencies: 'jsfingerprints' vs 'js_fingerprints' vs 'js_fingerprint', and the occasional use of 'find' instead of 'search' (e.g., find_js_fingerprint_similar_by_hash). This mixed style makes it hard to predict tool names.
With 128 tools, the server is severely over-scoped. Many tools could be combined (e.g., all search_jsfingerprints_by_* variants) or parameterized. The sheer number overwhelms an agent and suggests poor API design.
The core URL scanning workflow (submit, retrieve results, search, analyze) is well covered, including detailed sub-analyses like malware, YARA, and JS fingerprints. Minor gaps include no scan cancellation or user-specific scan listing, but overall coverage is strong.